Search NASA⌕ Search

SEARCH · Search NASA

Results for “microscopic analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30

Identifying Spectral Descriptors for Protonation in BaZr 0.8 Y 0.2 O 3-x with Electron Energy Loss Spectroscopy

Hydrogen economy is of paramount importance in the global transition to a sustainable, clean energy source that contributes to decarbonization efforts. In particular, the proton conducting proton ceramic fuel cells (PCFCs) play a crucial role in promoting hydrogen energy technology [1-5]. In a PCFC, the electrolyte is typically a solid oxide material that enables proton transport and can operate at temperatures lower than those of traditional oxygen ion conducting fuel cells [6]. The reduced operating temperature of PCFCs contributes to their durability, scalability, and efficiency [7,8]. BaZr 0.8 Y 0.2 O 3-x (BZY) is a promising proton conducting solid oxide electrolyte [9,10]. The emphasis on proton conductivity entails the importance of understanding proton content in the system. However, previous studies have largely relied on bulk techniques such as electrochemical impedance spectroscopy [7,11], Karl-Fischer titration [12,13], and thermogravimetric analysis [14] to obtain proton concentration. This is due to the small atomic size and light mass of hydrogen species making direct detection challenging. Bulk methods may be useful in estimating the proton content; however, it overlooks possible proton concentration gradient or segregation that may occur across or within a nanoparticle, especially when proton incorporation occurs nonuniformly through steam exposure on powder samples. In this paper, BZY is protonated at an estimated 0.15 mol of protons via steam exposure. Electron energy loss spectroscopy (EELS) with nanoscale spatial resolution is explored to identify proxy signals for proton detection using a JEOL ARM300 microscope operated at 300 kV with a Gatan GIF Continuum detector.

08 HYDROGEN↗

Giant kelp genetic monitoring before and after disturbance reveals stable genetic diversity in Southern California

Given the impacts of climate change and other anthropogenic stressors on marine systems, there is a need to accurately predict how species respond to changing environments and disturbance regimes. The use of genetic tools to monitor temporal trends in populations gives ecologists the ability to estimate changes in genetic diversity and effective population size that may be undetectable by traditional census methods. Although multiple studies have used temporal genetic analysis, they usually involve commercially important species, and rarely sample before and after disturbance. In this study, we run a temporal analysis of giant kelp, Macrocystis pyrifera , genetic diversity over the scope of 10 years (2008-2018) using the same microsatellite marker panel to assess the genetic consequences of disturbance in several populations of giant kelp ( Macrocystis pyrifera ) in the Southern California Bight. The study is a rare pre- and post-disturbance microsatellite analysis that included declines to giant kelp caused by the 2015/16 El Nino Southern Oscillation event. We used canopy biomass estimated by remote sensing (Landsat) to quantify the extent of disturbance to kelp beds, and sea surface temperature data to understand how kelp was pushed towards its temperature limits during this period. Despite prolonged periods with decreased canopy at several sites, no changes in genetic structure and allelic richness were observed. We argue that giant kelp in the region is best described as a “patchy population” system where true extinctions are rare. We discuss how deep refugia of subsurface sporophytes and cryptic microscopic life stages could have kept genetic diversity through disturbance. Given the increasing effects of climate change and uncertainty in modeling impacts of species with cryptic life history stages, we suggest further investigation to reveal the role such stages play in species resilience. Genetic monitoring studies of sites selected by remote census demographic and climate surveys should be continued in the future given the predicted impacts of climate change.

Klingbeil, III, William H.↗

Developing affordable and efficient heating devices for enhanced live cell imaging in confocal microscopy

Temperature control is crucial for live cell imaging, particularly in studies involving plant responses to high ambient temperatures and thermal stress. This study presents the design, development, and testing of two cost-effective heating devices tailored for confocal microscopy applications: an aluminum heat plate and a wireless mini-heater. The aluminum heat plate, engineered to integrate seamlessly with the standard 160 mm × 110 mm microscope stage, supports temperatures up to 36°C, suitable for studies in the range of non-stressful warm temperatures (e.g., 25-27°C forArabidopsis thaliana) and moderate heat stress (e.g., 30-36°C forA. thaliana). We also developed a wireless mini-heater that offers rapid, precise heating directly at the sample slide, with a temperature increase rate over 30 times faster than the heat plate. The wireless heater effectively maintained target temperatures up to 50°C, ideal for investigating severe heat stress and heat shock responses in plants. Both devices performed well in controlled studies, including the real-time analysis of heat shock protein accumulation and stress granule formation inA. thaliana. Our designs are effective and affordable, with total construction costs lower than $300. This accessibility makes them particularly valuable for small laboratories with limited funding. Future improvements could include enhanced heat uniformity, humidity control to mitigate evaporation, and more robust thermal management to minimize focus drift during extended imaging sessions. These modifications would further solidify the utility of our heating devices in live cell imaging, offering researchers reliable, budget-friendly tools for exploring plant thermal biology.

Plant Sciences↗

Phoebe: a high-performance framework for solving phonon and electron Boltzmann transport equations

Understanding the electrical and thermal transport properties of materials is critical to the design of electronics, sensors, and energy conversion devices. Computational modeling can accurately predict material properties but, in order to be reliable, requires accurate descriptions of electron and phonon states and their interactions. While first-principles methods are capable of describing the energy spectrum of each carrier, using them to compute transport properties is still a formidable task, both computationally demanding and memory intensive, requiring integration of fine microscopic scattering details for estimation of macroscopic transport properties. To address this challenge, we present Phoebe—a newly developed software package that includes the effects of electron–phonon, phonon–phonon, boundary, and isotope scattering in computations of electrical and thermal transport properties of materials with a variety of available methods and approximations. This open source C++ code combines MPI-OpenMP hybrid parallelization with GPU acceleration and distributed memory structures to manage computational cost, allowing Phoebe to effectively take advantage of contemporary computing infrastructures. We demonstrate that Phoebe accurately and efficiently predicts a wide range of transport properties, opening avenues for accelerated computational analysis of complex crystals.

36 MATERIALS SCIENCE↗

Time-Resolved X-ray Operando Observations of Lithiation Gradients across the Cathode Matrix and Individual Oxide Particles during Fast Cycling of a Li-Ion Cell

Lithiated transition metal oxides serve as active materials in the positive electrode (cathode) of lithium-ion cells. During electrochemical cycling, lithium ions intercalate and deintercalate into these oxide particles. This behavior causes two types of lithiation gradients to emerge: (i) a bulk gradient across the depth of the cathode matrix (averaged over individual oxide particles) and (ii) a microscopic gradient across the particles themselves, which also depends on their location in the electrode. Here we show how both gradients can be studied using operando X-ray diffraction during 4C charge and 4C discharge. The oxide (de)lithiation is estimated from the unit cell parameters by indexing the X-ray diffraction spectra. By fitting the lithiation profiles with orthogonal polynomials, the bulk gradients across the electrode thickness are quantified. These gradients develop as the current flows through the cell and dissipate during open-circuit and potentiostatic-hold periods. Further details of lithiation dynamics can be obtained through shape analysis of the Bragg peaks. In particular, from electrochemical model simulations, we show that the width and skewness of the (003) peak track (de)lithiation fronts moving across the individual oxide particles.

(003) peak↗

Controlling superconductivity of CeIrIn 5 microstructures by substrate selection

Superconductor/metal interfaces are usually fabricated in heterostructures that join these dissimilar materials. A conceptually different approach has recently exploited the strain sensitivity of heavy-fermion superconductors, selectively transforming regions of the crystal into the metallic state by strain gradients. The strain is generated by differential thermal contraction between the sample and the substrate. Here, we present an improved finite-element model that reliably predicts the superconducting transition temperature in CeIrIn 5 even in complex structures. Different substrates are employed to tailor the strain field into the desired shapes. Using this approach, both highly complex and strained as well as strain-free microstructures are fabricated to validate the model. This enables a high degree of control over the microscopic strain fields and forms the basis for more advanced structuring of superconductors as in Josephson junctions yet also finds natural use cases in any material class in which a modulation of the physical properties on a chip is desirable.

36 MATERIALS SCIENCE↗

Fundamental microscopic properties as predictors of large-scale quantities of interest: Validation through grain boundary energy trends

Correlations between fundamental microscopic properties computable from first principles, which we term canonical properties, and complex large-scale quantities of interest (QoIs) provide an avenue to predictive materials discovery. Here, we propose that such correlations can be efficiently discovered through simulations utilizing approximate interatomic potentials (IPs), which serve as an ensemble of “synthetic materials”. As a proof of principle we build a regression model relating canonical properties to the symmetric tilt grain boundary (GB) energy curves in face-centered cubic crystals, characterized by the scaling factor in the universal lattice matching model of Runnels et al. (2016), which we take to be our QoI. Our analysis recovers known correlations of GB energy to other properties and discovers new ones. We also demonstrate, using available density functional theory (DFT) GB energy data, that the regression model constructed from IP data is consistent with DFT results, confirming the assumption that the IPs and DFT belong to same statistical pool and thereby validating the approach. Regression models constructed in this fashion can be used to predict large-scale QoIs based on first-principles data and provide a general method for training IPs for QoIs beyond the scope of first-principles calculations.

36 MATERIALS SCIENCE↗

Low-temperature magnetic crossover in the topological kagome magnet TbMn 6 Sn 6

Magnetic topological phases of quantum matter are an emerging frontier in physics and materials science, of which kagome magnets appear as a highly promising platform. Here, we explore magnetic correlations in the recently identified topological kagome system TbMn6 S n 6 using muon spin rotation, combined with local field analysis and neutron diffraction. Our studies identify an out-of-plane ferrimagnetic structure with slow magnetic fluctuations which exhibit a critical slowing down below $T^{*}_{C1}$ ≃ 120 K and finally freeze into static patches with ideal out-of-plane order below T C1 ≃ 20 K. We further show that hydrostatic pressure of 2.1 GPa stabilises the static out-of-plane topological ferrimagnetic ground state in the whole volume of the sample. Therefore the exciting perspective arises of a magnetically-induced topological system whose magnetism can be controlled through external parameters. The present results will stimulate theoretical investigations to obtain a microscopic understanding of the relation between the low-temperature volume-wise magnetic evolution of the static c-axis ferrimagnetic patches and the topological electronic properties in TbMn 6 Sn 6 .

36 MATERIALS SCIENCE↗

Scaling CFB risers: Maintaining microstructure dynamics

Over the years there have been numerous approaches to develop a scaleup methodology for circulating fluidized beds. Many of these past approaches have relied on macroscopic definitions of similitude to define dimensionless groups such as Reynolds number, Froude number, density ratios, and dimensional ratios involving different length scales. These approaches have demonstrated various levels of success, but often fail when used outside the bounds of experimental datasets. The issue with these methods is that they rely on macroscopic similitude with the hopes that those conditions would provide microscopic similitude as it does in single phase systems where the Buckingham Pi techniques have given reasonable success. Two of the main reasons for failure are 1) changing fluidization regimes and 2) changing material properties that result in the material falling into a different Geldart group. Both are certain to change the microstructure (local instantaneous volume solids fraction) and changes to the microstructure affect the interphase transport properties of the reactor system, namely the mass transfer and heat transfer. Here, this work presents a new approach towards scaling based upon maintaining similitude at the microscale. It reviews a novel dimensionless flow regime map developed from analysis of the deterministic chaos parameters and higher order moments to ensure microstructure similitude. The work then examines four cases from the literature to assess the scaling approach used: (1) same particle-different scale risers for Geldart Group B particles, (2) Glicksman scaling of atmospheric circulating fluidized bed combustor, (3) same particle-different scale risers for Geldart Group A particles and (4) Glicksman scaling for pressurized gasification. General findings are that none of the scaling approaches produced directly applicable microstructure similar behavior based upon the chaotic and higher moment analysis. The positive take away is that the approach can define scale conditions that will provide similar microstructure that can be us to predict transport behavior.

42 ENGINEERING↗

Machine learning approaches to streamline and enhance the analysis of multiscale imaging data for bioaerosol and soil particles

Bioaerosol and soil particles are ubiquitous in the environment. They are multicomponent and complex in nature displaying mixed inorganic and organic components. The way components are mixed in a bioaerosol sample is referred to as its mixing state. Soil particles are also a mixture of inorganic (mineral) and organic (soil organic matter) components. Bioaerosol particles contribute to a major fraction of coarse mode atmospheric particles, especially in the tropical areas, contributing up to 80 % of the particle mass concentration. The mixing state of particles is crucial to evaluate because it impacts several important environmental processes such as warm and cold cloud formation and radiation budget. Mixing states in aerosols are accompanied by chemical reactions across solid-liquid-gas interfaces. In this study, we utilized elemental compositions and microcopy images of thousands of atmospheric particles acquired by computer-controlled scanning electron microscope equipped with an energy-dispersive x-ray spectrometer to compute the mixing state of atmospheric particles. A 2D convolutional neural network (CNN), also known as convnet, was used to model the relationship between low resolution imaging data and higher resolution spectroscopy data, with the former as training input and the latter as target output. Two types of CNNs were implemented and tested; a basic CNN and an Inception-v3 network. For binary classification, the basic CNN achieved an accuracy of 84.29 % across all atom types, and the Inception-v3-like network achieved an accuracy 85.51 %. This study demonstrates the applicability of deep learning to handle large amounts of imaging/chemical spectroscopy data efficiently and evaluate particle mixing state from a range of environmental samples.

54 ENVIRONMENTAL SCIENCES↗

Analysis of silica fouling on nonwetting surfaces

Ground water sources used as coolant fluids in a variety of thermal systems such as heat exchangers and power plant condensers contain silica particles that accrete on heat transfer surfaces over time leading to reduction in thermal performance, a problem that is particularly exacerbated with temperature. Nonwetting superhydrophobic, lubricant-infused, and a new class of solid-infused surfaces introduced in this work are candidates for fouling mitigation, by virtue of their water repellency, but little is known about fouling of silica on the surfaces, especially under dynamic flow conditions and as a function of temperature. This article presents, for the first time, a systematic study of dynamic flow fouling of silica on nonwetting surfaces vis-à-vis conventional copper surface over a temperature range 20–50°C. The mechanism of silica aggregate formation and its adherence to the different surfaces is elucidated by scanning electron microscope (SEM) imaging. Sigmoidal growth model is used to describe the time evolution of fouling thermal resistance and an Arrhenius model is presented for the temperature-dependent increase in the asymptotic fouling resistance on nonwetting and conventional surfaces alike. Lubricant-infused and solid-infused surfaces are shown to reduce fouling thermal resistance by up to 25% and 13%, respectively, compared to a conventional surface, whereas superhydrophobic surfaces lose their non-wettability under flow conditions, leading to an adverse increase in the fouling resistance by up to 13%. Considering the possible lubricant depletion in lubricant-infused surfaces over prolonged exposure to a flowing fluid, solid-infused surfaces present a robust alternative.

42 ENGINEERING↗

Design and Characterization of a Lens-Coupled System for Dynamic X-Ray Diffraction

X-ray diffraction (XRD) is a necessary technique for understanding states of materials under static and dynamic loading conditions. The higher-pressure Equation of State (EOS) of many materials can only be explored via shock or ramp compression at temperatures and pressures of interest. While static XRD work has yielded EOS measurements in the 100 - 200 GPa regime, dynamic X-ray diffraction (DXRD) can explore EOS phases in the TPa regime, which closely resembles inner-core planetary conditions. DXRD hinges on the ability to measure the exact phase or phase change of a material while under dynamic loading conditions. Macroscopic diagnostic systems (e.g. velocimetry and pyrometry) can infer a phase change but not identify the specific phase entered by a material. While microscopic (atomic-level) diagnostic systems (e.g. DXRD) have been designed and implemented in Department of Energy’s (DOE) National Laboratories complex, the unique nature of Sandia National Laboratories’ Pulsed Power Facility (Z Machine) prohibits the use of such devices. The destructive nature of Z experiments presents a challenge to data capture and retrieval. Furthermore there are electromagnetic interference, X-ray background, and mechanical constraints to consider. Thus, a multi-part X-ray diagnostic for use on the Z Machine and Z-Beamlet Laser system has been designed and analyzed. Portions of this new DYnamic SCintillator Optic (DYSCO) have been built, tested and fielded. A data analysis software has been written. Finally, the radiance profile of the DYSCO’s scintillator has been characterized through experiments performed at the University of Arizona.

36 MATERIALS SCIENCE↗

In situ investigation of ion irradiation-induced amorphization of (Ge 2 Sb 2 Te 5 ) 1−x C x [0 ≤ x ≤ 0.12]

Chalcogenide thin films that undergo reversible phase changes show promise for use in next-generation nanophotonics, microelectronics, and other emerging technologies. One of the many studied compounds, Ge2Sb2Te5, has demonstrated several useful properties and performance characteristics. However, the efficacy of benchmark Ge2Sb2Te5 is restricted by amorphous phase thermal stability below ∼150 °C, limiting its potential use in high-temperature applications. In response, previous studies have added a fourth species (e.g., C) to sputter-deposited Ge2Sb2Te5, demonstrating improved thermal stability. Our current research confirms reported thermal stability enhancements and assesses the effects of carbon on crystalline phase radiation response. Through in situ transmission electron microscope irradiation studies, we examine the effect of C addition on the amorphization behavior of initially cubic and trigonal polycrystalline films irradiated using 2.8 MeV Au to various doses up to 1 × 1015 cm −2 . It was found that increased C content reduces radiation tolerance of both cubic and trigonal phases.

36 MATERIALS SCIENCE↗

Neutron scattering study of magnetic anisotropy in the tetragonal antiferromagnet Bi 2 CuO 4

In this work, we present a comprehensive study of magnon excitations in the tetragonal easy-plane antiferromagnet Bi 2 CuO 4 using inelastic neutron scattering and spin-wave analyses. The nature of low-energy magnons, and hence the anisotropy in this material, has been controversial. We show unambiguously that the low-energy magnon spectrum consists of a gapped and a gapless mode, which we attribute to out-of-plane and in-plane spin fluctuations, respectively. We modeled the observed magnon spectrum using linear spin-wave analysis of a minimal anisotropic spin model motivated by the lattice symmetry. By studying the magnetic field dependence of the (1,0,0) Bragg peak intensity and the in-plane magnon intensity, we observed a spin-flop transition in the ab plane at ~0.4 T, which directly indicates the existence of a small in-plane anisotropy that is classically forbidden. It is only by taking into account magnon zero-point fluctuations beyond the linear spin-wave approximation that we could explain this in-plane anisotropy and its magnitude, the latter of which is deduced from the critical field of the spin-flop transition. The microscopic origins of the observed anisotropic interactions are also discussed. We found that our data are inconsistent with a large Dzyaloshinskii-Moriya interaction, which suggests a potential departure of Bi 2 CuO 4 from the conventional theories of magnetic anisotropy for other cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

In Situ Infrared Spectroscopy of a Plasma Jet and Data-Driven Solution of Multi-Scale Plasma Chemistry Problems

Multi-scale problems are commonly known in many scientific and engineering fields where microscopic behaviors are coupled with macroscopic processes. This is also an unsolved problem in low-temperature plasma chemistry where hundreds of chemical species are involved in thousands of chemical reactions. To address this problem, a physics-informed data-driven modeling is developed to solve such a multi-scale problem using the experimental Fourier-transform infrared spectroscopy (FTIR) measurements of several species’ concentrations. The modeling based on modern machine learning techniques provides concentrations of other relevant species along with the electron temperature and gas temperature at the location of FTIR measurements. For example, the concentrations O, OH, and H 2 O 2 play key roles in plasma-based cancer therapy. This approach overcomes the multi-scale difficulties of microscopic low-temperature plasma chemistry coupling with macroscopic gas flow and allows the acquisition of a full picture of output species concentrations. Presented here for the helium-air jet at atmospheric pressure, the ML-based modeling can be used to describe and possibly control multiscale systems using partial experimental data sets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Sodium Dodecyl Sulfate–Mediated Graphene Sensor for Electrochemical Detection of the Antibiotic Drug: Ciprofloxacin

The present study involves detecting and determining CIP by a new electrochemical sensor based on graphene (Gr) in the presence of sodium dodecyl sulfate (SDS) employing voltammetric techniques. Surface morphology studies of the sensing material were analyzed using a scanning electron microscope (SEM) and atomic force microscope (AFM). In the electroanalysis of CIP at the developed electrode, an enhanced anodic peak response was recorded, suggesting the electro-oxidation of CIP at the electrode surface. Furthermore, we evaluated the impact of the electrolytic solution, scan rate, accumulation time, and concentration variation on the electrochemical behavior of CIP. The possible electrode mechanism was proposed based on the acquired experimental information. A concentration variation study was performed using differential pulse voltammetry (DPV) in the lower concentration range, and the fabricated electrode achieved a detection limit of 2.9 × 10 -8 M. The proposed sensor detected CIP in pharmaceutical and biological samples. The findings displayed good recovery, with 93.8% for tablet analysis and 93.3% to 98.7% for urine analysis. The stability of a developed electrode was tested by inter- and intraday analysis.

36 MATERIALS SCIENCE↗

Optical potentials for the rare-isotope beam era

Abstract We review recent progress and motivate the need for further developments in nuclear optical potentials that are widely used in the theoretical analysis of nucleon elastic scattering and reaction cross sections. In regions of the nuclear chart away from stability, which represent a frontier in nuclear science over the coming decade and which will be probed at new rare-isotope beam facilities worldwide, there is a targeted need to quantify and reduce theoretical reaction model uncertainties, especially with respect to nuclear optical potentials. We first describe the primary physics motivations for an improved description of nuclear reactions involving short-lived isotopes, focusing on its benefits for fundamental science discoveries and applications to medicine, energy, and security. We then outline the various methods in use today to build optical potentials starting from phenomenological, microscopic, and ab initio methods, highlighting in particular, the strengths and weaknesses of each approach. We then discuss publicly-available tools and resources facilitating the propagation of recent progresses in the field to practitioners. Finally, we provide a set of open challenges and recommendations for the field to advance the fundamental science goals of nuclear reaction studies in the rare-isotope beam era. This paper is the outcome of the Facility for Rare Isotope Beams Theory Alliance (FRIB-TA) topical program ‘Optical Potentials in Nuclear Physics’ held in March 2022 at FRIB. Its content is non-exhaustive, was chosen by the participants and reflects their efforts related to optical potentials.

42 ENGINEERING↗

Resonant X-ray Diffraction Reveals the Location of Counterions in Doped Organic Mixed Ionic Conductors

Organic mixed ionic–electronic conductors (OMIECs) have the potential to enable diverse new technologies, ranging from novel in situ biosensors to flexible energy storage devices and neuromorphic computing platforms. However, their complex behavior in functional films involving electrolyte-induced swelling, ion ingress, and electrochemical doping inhibits rational material design. Of critical importance is an understanding of the specific location of the ions in the volumetrically doped material, yet this information is not readily available. Here, in this report, we present the use of grazing- incidence resonant X-ray diffraction (RXRD, also known as anomalous diffraction) at S and Cl K-edges to determine the structure of a doped, prototypical, semicrystalline polymer OMIEC based on oligo(ethylene glycol) substitution of regioregular polythiophene. The RXRD measurement provides two key insights. Quantitative analysis of the RXRD allows the determination of the position of the ion relative to the polymer backbone in the crystalline regions. We find that the anion is relatively distant from the backbone, nearer to the lamella mid-plane naively in conflict with expected Coulombic attraction between the ion and the doped polymer polaron. Comparison of RXRD to Cl – fluorescence (total Cl – ) allows determination of the relative order of doping between the crystalline and amorphous regions. We find preferential doping of the crystalline regions. Both insights, the preferential doping of crystals at low potential and the specific location of the counterion with respect to the polymer backbone, are critical to developing a microscopic understanding of transport in OMIECs.

36 MATERIALS SCIENCE↗